This data contains a comparison between the soil loss values we calculated using RUSLE and those produced by the Iowa State University's Daily Erosion Project (DEP). The comparison is done for almost 5,000 12-digit HUC's in Iowa, and parts of Minnesota, Nebraska, Kansas, and Missouri. The DEP uses the Water Erosion Prediction Project (WEPP) hillslope model with high temporal resolution, Next-Generation Weather 200 RADAR (NEXRAD) precipitation, and crop specific parameters such as C and P factors obtained from the confidential NRI database The comparison between RUSLE and DEP was made for HUC-12s with greater than 75% agricultural land cover. This threshold was used because DEP only models agricultural erosion, while our RUSLE-derived HUC-12 estimates include all land cover types. This data set corresponds to Fig 2 in the manuscript. This dataset is associated with the following publication: Woznicki, S., P. Cada, J. Wickham, M. Schmidt, J. Baynes, M. Mehaffey, and A. Neale. Sediment retention by natural landscapes in the conterminous United States. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 745: 140972, (2020).

This data contains a comparison between the soil loss values we calculated using RUSLE and those produced by the Iowa State University's Daily Erosion Project (DEP). The comparison is done for almost 5,000 12-digit HUC's in Iowa, and parts of Minnesota, Nebraska, Kansas, and Missouri. The DEP uses the Water Erosion Prediction Project (WEPP) hillslope model with high temporal resolution, Next-Generation Weather 200 RADAR (NEXRAD) precipitation, and crop specific parameters such as C and P factors obtained from the confidential NRI database The comparison between RUSLE and DEP was made for HUC-12s with greater than 75% agricultural land cover. This threshold was used because DEP only models agricultural erosion, while our RUSLE-derived HUC-12 estimates include all land cover types. This data set corresponds to Fig 2 in the manuscript. This dataset is associated with the following publication: Woznicki, S., P. Cada, J. Wickham, M. Schmidt, J. Baynes, M. Mehaffey, and A. Neale. Sediment retention by natural landscapes in the conterminous United States. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 745: 140972, (2020).

This data set gives estimates of erosion and sediment yield based on our study for the conterminous US by land cover class. The data correspond to Fig 4 in the manuscript. This dataset is associated with the following publication: Woznicki, S., P. Cada, J. Wickham, M. Schmidt, J. Baynes, M. Mehaffey, and A. Neale. Sediment retention by natural landscapes in the conterminous United States. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 745: 140972, (2020).

This data set gives estimates of erosion and sediment yield avoided due to the presence of natural land cover. These estimates are given for each land cover class and summarized for the conterminous US. The data correspond to Fig 6 in the manuscript. This dataset is associated with the following publication: Woznicki, S., P. Cada, J. Wickham, M. Schmidt, J. Baynes, M. Mehaffey, and A. Neale. Sediment retention by natural landscapes in the conterminous United States. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 745: 140972, (2020).

,RUSLE2 is a program used to evaluate potential erosion rates at specific sites as well as guide conservation and erosion control planning. It also provides economic information about fuel use and costs for specific crop management systems. The RUSLE2 site also supplies data files from their site that work together in these categories: Crop Management Zone, Climate, and Soil.,RUSLE2 uses factors based on climate, soil erodibility, topography, cover management and support practices to compute soil erosion. Conservation planning concepts must be understood and implemented into the RUSLE2 program in order for this program to be used effectively.,

The Revised Universal Soil Loss Equation (RUSLE) estimates the annual soil loss that is due to erosion using a factor-based approach with rainfall, soil erodibility, slope length, slope steepness and cover management and conservation practices as inputs. The collection is (i) a set of maps that represent the RUSLE factors, (ii) a map of the RUSLE estimates of soil erosion in Australia and (iii) a map of the uncertainty in the estimates of erosion.

This data set contains estimated average annual soil loss (Mg ha-1 yr-1) and estimated average annual sediment yield (Mg ha-1 yr-1) aggregated by HUC-12 watersheds for the conterminous US. This data set corresponds to Fig 3 in the manuscript. This dataset is associated with the following publication: Woznicki, S., P. Cada, J. Wickham, M. Schmidt, J. Baynes, M. Mehaffey, and A. Neale. Sediment retention by natural landscapes in the conterminous United States. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 745: 140972, (2020).

This data set contains estimated average annual soil loss avoided (Mg ha-1 yr-1) and estimated average annual sediment yield (Mg ha-1 yr-1) avoided aggregated by HUC-12 watersheds for the conterminous US. This data set corresponds to Fig 5 in the manuscript. This dataset is associated with the following publication: Woznicki, S., P. Cada, J. Wickham, M. Schmidt, J. Baynes, M. Mehaffey, and A. Neale. Sediment retention by natural landscapes in the conterminous United States. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 745: 140972, (2020).

This data set contains estimated average annual soil loss avoided (Mg ha-1 yr-1) and estimated average annual sediment yield (Mg ha-1 yr-1) avoided aggregated by HUC-12 watersheds for the conterminous US. This data set corresponds to Fig 5 in the manuscript. This dataset is associated with the following publication: Woznicki, S., P. Cada, J. Wickham, M. Schmidt, J. Baynes, M. Mehaffey, and A. Neale. Sediment retention by natural landscapes in the conterminous United States. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 745: 140972, (2020).

This table contains estimates for upland sediment erosion and delivery to the stream estimated using a modified Revised Universal Soil Loss Equation 2 (RUSLE2) approach (USDA-ARS, 2013). Upland erosion (Eu) was calculated as the sum of the product of the erosivity factor (Rm) estimated for each month, the soil erodibility factor (K), the length-slope factor (LS), C-factor (Cm) for each month, farming support practices (P) assumed to be 1, and the area of each land cover grouping in acres. Rasters with 10-m resolution were created for these five variables in the modified RUSLE2 equation to create an upland erosion (Eu) raster for the study area. Data were calculated for each National Hydrography (NHD) Dataset Version 1 catchment in the Difficult Run watershed.